Search results for: Successful Intelligence

Authors: Oliver F. Shyr, Yu-Hsuan Hsiao, David E. Andersson

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Due to the call of global warming effects, city planners aim at actions for reducing carbon emission. One of the approaches is to promote the usage of public transportation system toward the transit-oriented-development. For example, rapid transit system in Taipei city and Kaohsiung city are opening. However, until November 2008 the average daily patronage counted only 113,774 passengers at Kaohsiung MRT systems, much less than which was expected. Now the crucial questions: how the public transport competes with private transport? And more importantly, what factors would enhance the use of public transport? To give the answers to those questions, our study first applied regression to analyze the factors attracting people to use public transport around cities in the world. It is shown in our study that the number of MRT stations, city population, cost of living, transit fare, density, gasoline price, and scooter being a major mode of transport are the major factors. Subsequently, our study identified successful and unsuccessful cities in regard of the public transport usage based on the diagnosis of regression residuals. Finally, by comparing transportation strategies adopted by those successful cities, our conclusion stated that Kaohsiung City could apply strategies such as increasing parking fees, reducing parking spaces in downtown area, and reducing transfer time by providing more bus services and public bikes to promote the usage of public transport.

Keywords: Public Transit System, Comparative Study, Transport Demand Management, Regression

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Authors: Ali Aqa Mohammad Jawad

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Taking a relational approach, this paper analyzes the causal mechanisms associated with successful mobilization and rapid demobilization of the Enlightening Movement in post-2001 Afghanistan. The movement emerged after the state-owned Da Afghan Bereshna Sherkat (DABS) decided to divert the route for the Turkmenistan-Uzbekistan-Tajikistan-Afghanistan-Pakistan (TUTAP) electricity project. The grid was initially planned to go through the Hazara-inhabited province of Bamiyan, according to Afghanistan’s Power Sector Master Plan. The reroute served as an aide-mémoire of historical subordination to other ethno-religious groups for the Hazara community. It was also perceived as deprivation from post-2001 development projects, financed by international aid. This torched the accumulated grievances, which then gave birth to the Enlightening Movement. The movement had a successful mobilization. However, it demobilized after losing much of its mobilizing capabilities through an amalgamation of external and internal relational factors. The successful mobilization yet rapid demobilization constitutes the puzzle of this paper. From the theoretical perspective, this paper is significant as it establishes the applicability of contentious politics theory to protest mobilizations that occurred in Afghanistan, a context-specific, characterized by ethnic politics. Both primary and secondary data are utilized to address the puzzle. As for the primary resources, media coverage, interviews, reports, public media statements of the movement, involved in contentious performances, and data from Social Networking Services (SNS) are used. The covered period is from 2001-2018. As for the secondary resources, published academic articles and books are used to give a historical account of contentious politics. For data analysis, a qualitative comparative historical method is utilized to uncover the causal mechanisms associated with successful mobilization and rapid demobilization of the Movement. In this pursuit, both mobilization and demobilization are considered as larger political processes that could be decomposed to constituent mechanisms. Enlightening Movement’s framing and campaigns are first studied to uncover the associated mechanisms. Then, to avoid introducing some ad hoc mechanisms, the recurrence of mechanisms is checked against another case. Mechanisms qualify as robust if they are “recurrent” in different episodes of contention. Checking the recurrence of causal mechanisms is vital as past contentious events tend to reinforce future events. The findings of this paper suggest that the public sphere in Afghanistan is drastically different from Western democracies known as the birthplace of social movements. In Western democracies, when institutional politics did not respond, movement organizers occupied the public sphere, undermining the legitimacy of the government. In Afghanistan, the public sphere is ethicized. Considering the inter- and intra-relational dynamics of ethnic groups in Afghanistan, the movement reduced to an erosive inter- and intra-ethnic conflict. This undermined the cohesiveness of the movement, which then kicked-off its demobilization process.

Keywords: Enlightening movement, contentious politics, mobilization, demobilization.

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Authors: Ashly Joseph, Jithu Paulose

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Large language models (LLMs) have revolutionized natural language processing capabilities, enabling applications such as chatbots, dialogue agents, image, and video generators. Nevertheless, their trainings on extensive datasets comprising personal information poses notable privacy and safety hazards. This study examines methods for addressing these challenges, specifically focusing on approaches to enhance the security of LLM outputs, safeguard user privacy, and adhere to data protection rules. We explore several methods including post-processing detection algorithms, content filtering, reinforcement learning from human and AI inputs, and the difficulties in maintaining a balance between model safety and performance. The study also emphasizes the dangers of unintentional data leakage, privacy issues related to user prompts, and the possibility of data breaches. We highlight the significance of corporate data governance rules and optimal methods for engaging with chatbots. In addition, we analyze the development of data protection frameworks, evaluate the adherence of LLMs to General Data Protection Regulation (GDPR), and examine privacy legislation in academic and business policies. We demonstrate the difficulties and remedies involved in preserving data privacy and security in the age of sophisticated artificial intelligence by employing case studies and real-life instances. This article seeks to educate stakeholders on practical strategies for improving the security and privacy of LLMs, while also assuring their responsible and ethical implementation.

Keywords: Data privacy, large language models, artificial intelligence, machine learning, cybersecurity, general data protection regulation, data safety.

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: Human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence.

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Authors: Afrah Saad Mohsen Al-Mahfadi

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In rural areas of developing countries, participation of all stakeholders in water supply projects is an important step towards further development. As most of the beneficiaries are women, it is important that they should be involved to achieve successful and sustainable water supply projects. Women are responsible for the management of water both inside and outside home, and often spend more than six-hours a day fetching drinking water from distant water sources. The problem is that rural women play a role of little importance in the water supply projects’ phases in rural Yemen. Therefore, this research aimed at analyzing the different reasons of their lack of participation in projects and in what way a full participation -if achieved- could contribute to sustainable water supply projects in the rural mountainous areas in Yemen. Four water supply projects were selected as a case study in Al-Della'a Alaala sub-district in the Al-Mahweet governorate, two of them were implemented by the Social Fund and Development (SFD), while others were implemented by the General Authority for Rural Water Supply Projects (GARWSSP). Furthermore, the successful Al-Galba project, which is located in Badan district in Ibb governorate, was selected for comparison. The rural women's active participation in water projects have potential consequences including continuity and maintenance improvement, equipment security, and improvement in the overall health and education status of these areas. The majority of respondents taking part in GARWSSP projects estimated that there is no reason to involve women in the project activities. In the comparison project - in which a woman worked as a supervisor and implemented the project – all respondents indicated that the participation of women is vital for sustainability. Therefore, the results of this research are intended to stimulate rural women's participation in the mountainous areas of Yemen.

Keywords: Assessment, rural woman, sustainability, water management.

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Authors: Tshimangadzo Oscar Magadze

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For successful re-integration, the individual offender must adapt and transform, which requires that the offender should adopt and internalise socially approved norms, attitudes, values, and beliefs. However, the offender’s labelling and community stigmatisation decide the destination of the offender. Community involvement in ex-offenders’ re-integration is an important issue in efforts to reduce recidivism and to control overcrowding in our correctional facilities. Crime is a social problem that requires society to come together to fight against it. This study was conducted in the Limpopo Province in Vhembe District Municipality within four local municipalities, namely Musina, Makhado, Mutale, and Thulamela. A total number of 30 participants were interviewed, and all were members of the Community Corrections Forums. This was necessitated by the fact that Musina is a very small area, which compelled the Department of Correctional Services to combine the two (Musina and Makhado) into one social re-integration entity. This is a qualitative research study where participants were selected through the use of purposive sampling. Participants were selected based on the value they would add to this study in order to achieve the objectives. The data collection method of this study was the focus group, which comprised of three groups of 10 participants each. Thulamela and Mutale local municipalities formed a group with (10) participants each, whereas Musina (2) and Makhado (8) formed another. Results indicate that the current situation is not conducive for re-integration to be successful. Participants raised many factors that need serious redress, namely offenders’ discrimination, lack of forgiveness by members of the community, which is fuelled by lack of community awareness due to the failure of the Department of Correctional Services in educating communities on ex-offenders’ re-integration.

Keywords: Ex-offender, labelling, re-integration, stigmatisation.

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Authors: A. Sherif, H. Sabry, A. Elzafarany, M. Gadelhak, R. Arafa, M. Aly

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This paper addresses the design of hospital Intensive Care Unit windows for the achievement of visual comfort and energy savings. The aim was to identify the window size and shading system configurations that could fulfill daylighting adequacy, avoid glare and reduce energy consumption. The study focused on addressing the effect of utilizing different shading systems in association with a range of Window-to-Wall Ratios (WWR) in different orientations under the desert clear-sky of Cairo, Egypt. The results of this study demonstrated that solar penetration is a critical concern affecting the design of ICU windows in desert locations, as in Cairo, Egypt. Use of shading systems was found to be essential in providing acceptable daylight performance and energy saving. Careful positioning of the ICU window towards a proper orientation can dramatically improve performance. It was observed that ICU windows facing the north direction enjoyed the widest range of successful window configuration possibilities at different WWRs. ICU windows facing south enjoyed a reasonable number of configuration options as well. By contrast, the ICU windows facing the east orientation had a very limited number of options that provide acceptable performance. These require additional local shading measures at certain times due to glare incidence. Moreover, use of horizontal sun breakers and solar screens to protect the ICU windows proved to be more successful than the other alternatives in a wide range of Window to Wall Ratios. By contrast, the use of light shelves and vertical shading devices seemed questionable.

Keywords: Daylighting, Desert, Energy Efficiency, Shading.

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Authors: Magdi Elmessiry, Adel Elmessiry

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The fashion industry represents a significant portion of the global gross domestic product, however, it is plagued by cheap imitators that infringe on the trademarks which destroys the fashion industry's hard work and investment. While eventually the copycats would be found and stopped, the damage has already been done, sales are missed and direct and indirect jobs are lost. The infringer thrives on two main facts: the time it takes to discover them and the lack of tracking technologies that can help the consumer distinguish them. Blockchain technology is a new emerging technology that provides a distributed encrypted immutable and fault resistant ledger. Blockchain presents a ripe technology to resolve the infringement epidemic facing the fashion industry. The significance of the study is that a new approach leveraging the state of the art blockchain technology coupled with artificial intelligence is used to create a framework addressing the fashion infringement problem. It transforms the current focus on legal enforcement, which is difficult at best, to consumer awareness that is far more effective. The framework, Crypto CopyCat, creates an immutable digital asset representing the actual product to empower the customer with a near real time query system. This combination emphasizes the consumer's awareness and appreciation of the product's authenticity, while provides real time feedback to the producer regarding the fake replicas. The main findings of this study are that implementing this approach can delay the fake product penetration of the original product market, thus allowing the original product the time to take advantage of the market. The shift in the fake adoption results in reduced returns, which impedes the copycat market and moves the emphasis to the original product innovation.

Keywords: Fashion, infringement, Blockchain, artificial intelligence, textiles supply.

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Authors: Omid F. Valilai, Mahmoud Houshmand

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Nowadays companies strive to survive in a competitive global environment. To speed up product development/modifications, it is suggested to adopt a collaborative product development approach. However, despite the advantages of new IT improvements still many CAx systems work separately and locally. Collaborative design and manufacture requires a product information model that supports related CAx product data models. To solve this problem many solutions are proposed, which the most successful one is adopting the STEP standard as a product data model to develop a collaborative CAx platform. However, the improvement of the STEP-s Application Protocols (APs) over the time, huge number of STEP AP-s and cc-s, the high costs of implementation, costly process for conversion of older CAx software files to the STEP neutral file format; and lack of STEP knowledge, that usually slows down the implementation of the STEP standard in collaborative data exchange, management and integration should be considered. In this paper the requirements for a successful collaborative CAx system is discussed. The STEP standard capability for product data integration and its shortcomings as well as the dominant platforms for supporting CAx collaboration management and product data integration are reviewed. Finally a platform named LAYMOD to fulfil the requirements of CAx collaborative environment and integrating the product data is proposed. The platform is a layered platform to enable global collaboration among different CAx software packages/developers. It also adopts the STEP modular architecture and the XML data structures to enable collaboration between CAx software packages as well as overcoming the STEP standard limitations. The architecture and procedures of LAYMOD platform to manage collaboration and avoid contradicts in product data integration are introduced.

Keywords: CAx, Collaboration management, STEP applicationmodules, STEP standard, XML data structures

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Authors: Carsten Röcker

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This paper reports on a survey of state-of-the-art application scenarios for smart office environments. Based on an analysis of ongoing research activities and industry projects, functionalities and services of future office systems are extracted. In a second step, these results are used to identify the key characteristics of emerging products.

Keywords: Ambient Intelligence, Ubiquitous Computing, Smart Office Environments, Application Scenarios.

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Authors: Isaac Kofi Mensah

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Governments around the world are adopting Information and Communication Technologies (ICTs) because of the important opportunities it provides through E-government (EG) to modernize government public administration processes and delivery of quality and efficient public services. Almost every country in the world is adopting ICT in its public sector administration (EG) to modernize and change the traditional process of government, increase citizen engagement and participation in governance, as well as the provision of timely information to citizens. This paper, therefore, seeks to present the adoption, development and implementation of EG in regions globally, as well as the ICT indicators around the world, which are making EG initiatives successful. Europe leads the world in its EG adoption and development index, followed by the Americas, Asia, Oceania and Africa. There is a gradual growth in ICT indicators in terms of the increase in Internet access and usage, increase in broadband penetration, an increase of individuals using the Internet at home and a decline in fixed telephone use, while the mobile cellular phone has been on the increase year-on-year. Though the lack of ICT infrastructure is a major challenge to EG adoption and implementation around the world, in Africa it is very pervasive, hampering the expansion of Internet access and provision of broadband, and hence is a barrier to the successful adoption, development, and implementation of EG initiatives in countries on the continent. But with the general improvement and increase in ICT indicators around the world, it provides countries in Europe, Americas, Asia, Arab States, Oceania and Africa with the huge opportunity to enhance public service delivery through the adoption of EG. Countries within these regions cannot fail their citizens who desire to enjoy an enhanced and efficient public service delivery from government and its many state institutions.

Keywords: E-government development index, e-government, indicators, information and communication technologies.

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.

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Authors: Berardina De Carolis, Giovanni Cozzolongo

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In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.

Keywords: Ambient intelligence, agent-based systems, influence diagrams.

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Authors: Ivayla Trifonova, Naoum Jamous, Holger Schrödl

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A good web design is a prerequisite for a successful business nowadays, especially since the internet is the most common way for people to inform themselves. Web design includes the optical composition, the structure, and the user guidance of websites. The importance of each website leads to the question if there is a way to measure its usefulness. The aim of this paper is to suggest a methodology for the evaluation of web design. The desired outcome is to have an evaluation that is concentrated on a specific website and its target group.

Keywords: Evaluation methodology, factor analysis, target group, web design.

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Authors: Y. Bek-Ali, K. Gabdullin

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This paper explores transformation of higher education system in Kazakhstan since 1991. The research unravels successful experience in the field and challenges. It covers issues of institutional change, faculty, research, university, funding, standards and leadership. The paper offers recommendations in improving state of art in higher educational institutions of Kazakhstan based on international approaches and local realities.

Keywords: higher educational institution, Kazakhstan, transformation

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Authors: Samuel Carpintero

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Public-private partnerships (PPP) arrangements have been extensively used in Canada, where the participation of private companies in financing and managing infrastructure projects has increased significantly in the last decade, particularly in the transportation sector. This paper analyses the evolution of the PPP market for transportation projects in Canada and examines the participation of Spanish developers in this market, which have been particularly successful in winning PPP contracts during the last decade.

Keywords: PPP, concession, infrastructure, construction.

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Authors: Mafawez Alharbi, Mahdi Jemmali

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E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: Artificial intelligence, architecture, e-learning, software engineering, processing.

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Authors: Pinaki Pratim Acharjya, Dibyendu Ghoshal

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Image matching methods play a key role in deciding correspondence between two image scenes. This paper presents a method for the matching of digital images using mathematical morphology. The proposed method has been applied to real life images. The matching process has shown successful and promising results.

Keywords: Digital image, gradients, image matching, mathematical morphology.

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Authors: Shattyk Aliyev, Zhakypbek Altayev, Zuchra Ismagambetova, Yerkin Massanov

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Information society is an absolutely new public formation at which the infrastructure and the social relations correspond to the socialized essence of «information genotype» mankind. Information society is a natural social environment which allows the person to open completely the information nature, to use intelligence for joint creation with other people of new information on the basis of knowledge earlier saved up by previous generations.

Keywords: Information society, Philosophy, Education, Globalization and innovation.

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Authors: Andrey V. Timofeev

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This paper presents development results of the method of seismoacoustic activity monitoring based on usage vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes, which take place due to microscopic seismoacoustic impacts on the optical fiber, allows to determine seismoacoustic emission sources positions and to identify their types. Results of using this approach are successful for complex monitoring of railways.

Keywords: C-OTDR systems, monitoring of railways, Rayleigh backscattering.

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Authors: Sitalakshmi Venkataraman

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Recent scientific investigations indicate that multimodal biometrics overcome the technical limitations of unimodal biometrics, making them ideally suited for everyday life applications that require a reliable authentication system. However, for a successful adoption of multimodal biometrics, such systems would require large heterogeneous datasets with complex multimodal fusion and privacy schemes spanning various distributed environments. From experimental investigations of current multimodal systems, this paper reports the various issues related to speed, error-recovery and privacy that impede the diffusion of such systems in real-life. This calls for a robust mechanism that caters to the desired real-time performance, robust fusion schemes, interoperability and adaptable privacy policies. The main objective of this paper is to present a framework that addresses the abovementioned issues by leveraging on the heterogeneous resource sharing capacities of Grid services and the efficient machine learning capabilities of artificial neural networks (ANN). Hence, this paper proposes a Grid-based neural network framework for adopting multimodal biometrics with the view of overcoming the barriers of performance, privacy and risk issues that are associated with shared heterogeneous multimodal data centres. The framework combines the concept of Grid services for reliable brokering and privacy policy management of shared biometric resources along with a momentum back propagation ANN (MBPANN) model of machine learning for efficient multimodal fusion and authentication schemes. Real-life applications would be able to adopt the proposed framework to cater to the varying business requirements and user privacies for a successful diffusion of multimodal biometrics in various day-to-day transactions.

Keywords: Back Propagation, Grid Services, MultimodalBiometrics, Neural Networks.

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Authors: Corneliu Sofronie, Roxana Zubcov

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Cognitive Science appeared about 40 years ago, subsequent to the challenge of the Artificial Intelligence, as common territory for several scientific disciplines such as: IT, mathematics, psychology, neurology, philosophy, sociology, and linguistics. The new born science was justified by the complexity of the problems related to the human knowledge on one hand, and on the other by the fact that none of the above mentioned sciences could explain alone the mental phenomena. Based on the data supplied by the experimental sciences such as psychology or neurology, models of the human mind operation are built in the cognition science. These models are implemented in computer programs and/or electronic circuits (specific to the artificial intelligence) – cognitive systems – whose competences and performances are compared to the human ones, leading to the psychology and neurology data reinterpretation, respectively to the construction of new models. During these processes if psychology provides the experimental basis, philosophy and mathematics provides the abstraction level utterly necessary for the intermission of the mentioned sciences. The ongoing general problematic of the cognitive approach provides two important types of approach: the computational one, starting from the idea that the mental phenomenon can be reduced to 1 and 0 type calculus operations, and the connection one that considers the thinking products as being a result of the interaction between all the composing (included) systems. In the field of psychology measurements in the computational register use classical inquiries and psychometrical tests, generally based on calculus methods. Deeming things from both sides that are representing the cognitive science, we can notice a gap in psychological product measurement possibilities, regarded from the connectionist perspective, that requires the unitary understanding of the quality – quantity whole. In such approach measurement by calculus proves to be inefficient. Our researches, deployed for longer than 20 years, lead to the conclusion that measuring by forms properly fits to the connectionism laws and principles.

Keywords: complementary methodology, connection approach, networks without scaling, quantum psychology.

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Authors: A. Schuster

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Many artificial intelligence (AI) techniques are inspired by problem-solving strategies found in nature. Robustness is a key feature in many natural systems. This paper studies robustness in artificial neural networks (ANNs) and proposes several novel, nature inspired ANN architectures. The paper includes encouraging results from experimental studies on these networks showing increased robustness.

Keywords: robustness, robust artificial neural networks architectures.

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Authors: Emilia Nercissians

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The paper attempts to contribute to the largely neglected social and anthropological discussion of technology development on the one hand, and to redirecting the emphasis in anthropology from primitive and exotic societies to problems of high relevance in contemporary era and how technology is used in everyday life. It draws upon multidimensional models of intelligence and ideal type formation. It is argued that the predominance of computational and cognitive cosmovisions have led to technology alienation. Injection of communicative competence in artificially intelligent systems and identity technologies in the coming information society are analyzed

Keywords: convergence, nomadic computing, solidarity, status.

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Authors: Luc Cessieux, French Navy, Adrien Derock, DCNS/IMATH

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Security risk models have been successful in estimating the likelihood of attack for simple security threats. However, modeling complex system and their security risk is even a challenge. Many methods have been proposed to face this problem. Often difficult to manipulate, and not enough all-embracing they are not as famous as they should with administrators and deciders. We propose in this paper a new tool to model big systems on purpose. The software, takes into account attack threats and security strength.

Keywords: Security, risk management, threat, modelization.

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Authors: A. Otjen, S. Keller

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A Montana university has used applied consumer research in experiential learning with non-profit clients for over a decade. Through trial and error, a successful protocol has been established from problem statement through formative research to integrated marketing campaign execution. In this paper, we describe the protocol and its applications. Analysis was completed to determine the effectiveness of the campaigns and the results of how pre- and post-consumer research mark societal change because of media.

Keywords: Marketing, experiential learning, consumer behavior, community partner.

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra, Abdus Sobur

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of artificial intelligence (AI), specifically deep learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images, representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our approach presents a hybrid model, amalgamating the strengths of two renowned convolutional neural networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: Artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging.

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

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AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: Touching interaction, ambient intelligence, NFC, RFID.

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Authors: I. Elrouby

Abstract:

The continued growth of tourism in the future relies on maintaining a clean environment by achieving sustainable development. The erosion and degradation of beaches, the deterioration of coastal water quality, visual pollution of coastlines by massive developments, all this has contributed heavily to the loss of the natural attractiveness for tourism. In light of this, promoting the concept of sustainable coastal development is becoming a central goal for governments and private sector. An ecolodge is a small hotel or guesthouse that incorporates local architectural, cultural and natural characteristics, promotes environmental conservation through minimizing the use of waste and energy and produces social and economic benefits for local communities. Egypt has some scattered attempts in some areas like Sinai in the field of ecolodging. This research tends to investigate the potentials of the North West Coast (NWC) in Alexandria as a new candidate for ecolodging investments. The area is full of primitive natural and man-made resources. These, if used in an environmental-friendly way could achieve cost reductions as a result of successful resource management for investors on the one hand, and coastal preservation on the other hand. In-depth interviews will be conducted with stakeholders in the tourism sector to examine their opinion about the potentials of the research area for ecolodging developments. The candidates will be also asked to rate the importance of the availability of certain environmental aspects in such establishments such as the uses of resources that originate from local communities, uses of natural power sources, uses of an environmental-friendly sewage disposal, forbidding the use of materials of endangered species and enhancing cultural heritage conservation. The results show that the area is full of potentials that could be effectively used for ecolodging investments. This if efficiently used could attract ecotourism as a supplementary type of tourism that could be promoted in Alexandria aside cultural, recreational and religious tourism.

Keywords: Alexandria, ecolodging, ecotourism, sustainability.

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Authors: K. Liagkouras, K. Metaxiotis

Abstract:

Customer relationship management (CRM) systems in business are a reality of the contemporary business world for the last decade or so. Still, there are grey areas regarding the successful implementation and operation of CRM systems in business. This paper, through the systematic study of the CRM implementation paradigm, attempts to identify the most important challenges and opportunities that the CRM systems face in a rapidly changing business world.

Keywords: Customer Relationship Management, CRM, Business, Information Systems.

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